from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting(against_lib="sklearnex", config="config.yml")
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.212 | 0.0 | -1 | 1 | NaN | 0.045 | 0.001 | 0.245 | 0.245 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.518 | 0.0 | -1 | 5 | NaN | 0.045 | 0.000 | 0.238 | 0.238 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.498 | 0.0 | 1 | 100 | NaN | 0.045 | 0.000 | 0.237 | 0.237 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.478 | 0.0 | -1 | 100 | NaN | 0.045 | 0.000 | 0.238 | 0.238 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.458 | 0.0 | 1 | 5 | NaN | 0.045 | 0.000 | 0.237 | 0.237 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.548 | 0.0 | 1 | 1 | NaN | 0.044 | 0.000 | 0.238 | 0.238 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.406 | 0.0 | -1 | 1 | NaN | 0.008 | 0.000 | 0.525 | 0.525 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.419 | 0.0 | -1 | 5 | NaN | 0.007 | 0.000 | 0.514 | 0.514 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.411 | 0.0 | 1 | 100 | NaN | 0.008 | 0.000 | 0.516 | 0.516 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.414 | 0.0 | -1 | 100 | NaN | 0.007 | 0.000 | 0.519 | 0.519 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.409 | 0.0 | 1 | 5 | NaN | 0.008 | 0.000 | 0.520 | 0.520 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.420 | 0.0 | 1 | 1 | NaN | 0.008 | 0.000 | 0.505 | 0.505 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.985 | 0.084 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.171 | 0.003 | 11.623 | 11.625 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.003 | NaN | 0.000 | 0.022 | -1 | 1 | 1.000 | 0.009 | 0.000 | 2.589 | 2.590 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.737 | 0.073 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.172 | 0.002 | 15.875 | 15.876 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | NaN | 0.000 | 0.023 | -1 | 5 | 1.000 | 0.008 | 0.000 | 2.773 | 2.773 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.914 | 0.003 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.208 | 0.001 | 9.220 | 9.220 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | NaN | 0.000 | 0.019 | 1 | 100 | 1.000 | 0.009 | 0.000 | 2.242 | 2.243 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.721 | 0.056 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.209 | 0.001 | 13.023 | 13.024 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | NaN | 0.000 | 0.023 | -1 | 100 | 1.000 | 0.009 | 0.001 | 2.629 | 2.645 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.890 | 0.004 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.173 | 0.003 | 10.924 | 10.925 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | NaN | 0.000 | 0.019 | 1 | 5 | 1.000 | 0.008 | 0.000 | 2.242 | 2.243 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.140 | 0.002 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.171 | 0.002 | 6.657 | 6.658 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.001 | NaN | 0.000 | 0.019 | 1 | 1 | 1.000 | 0.009 | 0.000 | 2.163 | 2.163 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.764 | 0.017 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.025 | 0.000 | 70.335 | 70.340 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.002 | NaN | 0.000 | 0.004 | -1 | 1 | 1.000 | 0.001 | 0.000 | 6.734 | 6.787 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.588 | 0.028 | NaN | 0.000 | 0.003 | -1 | 5 | 0.922 | 0.026 | 0.000 | 100.061 | 100.067 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.005 | NaN | 0.000 | 0.006 | -1 | 5 | 1.000 | 0.001 | 0.000 | 10.491 | 10.550 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.840 | 0.008 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.058 | 0.002 | 31.484 | 31.499 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 3.875 | 3.910 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.613 | 0.021 | NaN | 0.000 | 0.003 | -1 | 100 | 0.929 | 0.058 | 0.000 | 45.268 | 45.269 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 8.990 | 9.036 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.813 | 0.001 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.028 | 0.002 | 65.478 | 65.581 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 4.146 | 4.165 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.053 | 0.002 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.025 | 0.000 | 41.395 | 41.402 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 2.673 | 2.690 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.051 | 0.083 | NaN | 0.026 | 0.0 | -1 | 1 | NaN | 0.757 | 0.048 | 4.029 | 4.038 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.844 | 0.041 | NaN | 0.021 | 0.0 | -1 | 5 | NaN | 0.743 | 0.003 | 5.176 | 5.176 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.901 | 0.085 | NaN | 0.021 | 0.0 | 1 | 100 | NaN | 0.736 | 0.010 | 5.297 | 5.298 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.824 | 0.096 | NaN | 0.021 | 0.0 | -1 | 100 | NaN | 0.745 | 0.012 | 5.130 | 5.131 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.596 | 0.080 | NaN | 0.022 | 0.0 | 1 | 5 | NaN | 0.726 | 0.012 | 4.952 | 4.952 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.735 | 0.131 | NaN | 0.021 | 0.0 | 1 | 1 | NaN | 0.746 | 0.009 | 5.009 | 5.009 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.021 | 0.0 | -1 | 1 | NaN | 0.005 | 0.003 | 0.172 | 0.205 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | -1 | 5 | NaN | 0.003 | 0.003 | 0.180 | 0.240 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.029 | 0.0 | 1 | 100 | NaN | 0.001 | 0.001 | 0.502 | 0.674 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | 0.634 | 0.639 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | 0.656 | 0.657 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | 0.676 | 0.676 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.852 | 1.103 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.116 | 0.003 | 7.334 | 7.337 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 10.082 | 10.631 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.133 | 0.526 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.207 | 0.002 | 5.486 | 5.486 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 8.194 | 8.702 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.661 | 0.780 | NaN | 0.000 | 0.006 | 1 | 100 | 0.951 | 0.621 | 0.011 | 9.110 | 9.111 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 4.377 | 4.626 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.238 | 0.356 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.611 | 0.007 | 5.298 | 5.298 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | NaN | 0.000 | 0.005 | -1 | 100 | 1.000 | 0.001 | 0.000 | 6.392 | 6.782 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.758 | 0.540 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.211 | 0.006 | 8.313 | 8.316 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | NaN | 0.000 | 0.002 | 1 | 5 | 1.000 | 0.000 | 0.000 | 3.970 | 4.255 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.930 | 0.282 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.115 | 0.003 | 8.056 | 8.060 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 3.740 | 4.037 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.027 | 0.023 | NaN | 0.001 | 0.000 | -1 | 1 | 0.891 | 0.000 | 0.000 | 66.295 | 66.843 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 1 | 1.000 | 0.000 | 0.000 | 24.164 | 25.156 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.001 | NaN | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 37.654 | 37.671 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.000 | 0.000 | 23.874 | 25.198 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.039 | 0.016 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.004 | 0.000 | 8.852 | 8.852 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 5.926 | 6.194 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.007 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.005 | 0.000 | 6.757 | 6.774 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.000 | 0.000 | 20.687 | 21.822 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 31.911 | 31.921 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 6.503 | 6.897 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.000 | 0.000 | 48.408 | 48.491 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 6.745 | 7.155 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.598 | 0.243 | 30 | 0.027 | 0.0 | random | NaN | 0.366 | 0.031 | 1.633 | 1.639 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.598 | 0.119 | 30 | 0.027 | 0.0 | k-means++ | NaN | 0.394 | 0.018 | 1.519 | 1.520 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.581 | 0.192 | 30 | 0.143 | 0.0 | random | NaN | 2.562 | 0.055 | 2.178 | 2.179 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.725 | 0.031 | 30 | 0.140 | 0.0 | k-means++ | NaN | 2.717 | 0.050 | 2.107 | 2.108 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.010 | 0.000 | random | 0.001 | 0.0 | 0.0 | 9.009 | 12.907 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 1.000 | 0.0 | 0.0 | 8.755 | 14.661 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.001 | 0.000 | 30 | 0.011 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 11.013 | 12.696 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | k-means++ | 1.000 | 0.0 | 0.0 | 12.798 | 13.472 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.451 | 0.000 | random | 0.002 | 0.0 | 0.0 | 6.808 | 7.432 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | random | 1.000 | 0.0 | 0.0 | 11.830 | 11.997 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.437 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 6.962 | 7.554 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | k-means++ | 1.000 | 0.0 | 0.0 | 13.569 | 14.012 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.074 | 0.003 | 20 | 0.002 | 0.0 | random | NaN | 0.026 | 0.002 | 2.860 | 2.870 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.206 | 0.002 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.078 | 0.000 | 2.632 | 2.632 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.190 | 0.004 | 20 | 0.042 | 0.0 | random | NaN | 0.104 | 0.002 | 1.830 | 1.830 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.547 | 0.007 | 20 | 0.015 | 0.0 | k-means++ | NaN | 0.280 | 0.004 | 1.952 | 1.952 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.010 | 0.000 | random | 0.000 | 0.000 | 0.0 | 4.027 | 4.038 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 1.000 | 0.000 | 0.0 | 12.651 | 12.985 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | k-means++ | 0.001 | 0.000 | 0.0 | 3.847 | 3.873 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 1.000 | 0.000 | 0.0 | 12.938 | 13.332 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.344 | 0.000 | random | 0.279 | 0.001 | 0.0 | 2.583 | 2.594 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | random | 1.000 | 0.000 | 0.0 | 9.159 | 9.305 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.344 | 0.000 | k-means++ | 0.317 | 0.001 | 0.0 | 2.516 | 2.527 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | k-means++ | 1.000 | 0.000 | 0.0 | 9.407 | 9.604 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 10.654 | 0.40 | [20] | 0.075 | 0.000 | NaN | NaN | NaN | NaN | NaN | 1.947 | 0.040 | 5.473 | 5.474 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.060 | 0.91 | [26] | 0.075 | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.017 | 0.025 | 1.042 | 1.042 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.001 | [20] | 1.995 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.549 | 1.138 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.017 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 0.354 | 0.359 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.000 | [26] | 5.126 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.004 | 0.001 | 0.373 | 0.392 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | [26] | 1.092 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.001 | 0.000 | 0.111 | 0.121 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.171 | 0.004 | NaN | 0.467 | 0.0 | NaN | NaN | NaN | 0.179 | 0.001 | 0.957 | 0.957 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.148 | 0.172 | NaN | 0.697 | 0.0 | NaN | NaN | NaN | 0.313 | 0.275 | 3.673 | 4.890 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | NaN | 6.944 | 0.0 | NaN | NaN | 0.083 | 0.018 | 0.0 | 0.630 | 0.630 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | NaN | 1.439 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.663 | 0.735 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | NaN | 5.315 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.458 | 0.721 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | NaN | 0.019 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.600 | 0.640 | See | See |